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Spiideo SoccerNet SynLoc: Single Frame World Coordinate Athlete Detection and Localization with Synthetic Data

Currently, most research and public datasets for video sports analytics are base on detecting players as bounding boxes in broadcast videos. Going from there to precise locations on the pitch is however hard. Modern solutions are making dedicated static cameras covering the entire pitch more readily accessible, and they are now used more and more even in lower tiers. To promote research that can take benefits of such cameras and produce more precise pitch locations, we introduce the Spiideo SoccerNet SynLoc dataset. It consists of synthetic athletes rendered on top of images from real world installation of such cameras. We also introduce a new task of detecting the players in the world pitch coordinate system and a new metric based solely on real world physical properties where the representation in the image is irrelevant. The dataset and code are publicly available at https://github. com/Spiideo/sskit.

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